Eman Sedqy Shlkamy
2026
From Posts to Pressure: An Arabic Dataset about Stress and Mental-Health Monitoring
Wajdi Zaghouani | Eman Sedqy Shlkamy | Mabrouka Bessghaier
Proceedings of the 2nd Workshop on NLP for Languages Using Arabic Script
Wajdi Zaghouani | Eman Sedqy Shlkamy | Mabrouka Bessghaier
Proceedings of the 2nd Workshop on NLP for Languages Using Arabic Script
How do Arabic-speaking communities express and engage with psychological stress on social media? We introduce AraStress, the first large-scale Arabic corpus dedicated to psychological stress research, comprising 175,862 public social media posts from 2020 to 2024, covering pandemic and post-pandemic periods.It fills a significant gap in Arabic mental-health NLP resources focused on stress, enabling large-scale analysis of related expressions.Unlike prior work focusing primarily on Twitter and depression or suicidality, AraStress addresses the critical gap in stress-focused resources. Our lexicon-based analysis reveals that stress-related posts elicit predominantly affective engagement and exhibit a hybrid lexical framing that integrates religious and therapeutic language. AraStress provides a foundational resource for culturally grounded computational models of stress detection and digital wellbeing in Arabic-speaking communities.